Menlo Security is the leader in Browser Security for human and agentic workforces. Our mission is to enable humans and agents to connect, communicate, and collaborate securely, without compromise. The Menlo Browser Security Platform protects organizations from cyberattacks by stopping threats across the web, documents, and email before they reach the user. With Menlo Agent Runtime Security (MARS), that protection now extends to the AI agents working alongside every employee. Menlo Security is trusted by major global businesses, including Fortune 500 companies and government agencies, to protect their most valuable asset, their data, and is backed by top-tier investors.

Summary

We're looking for a forward-thinking Security Engineer to join our security team, focused on offensive and defensive testing, penetration testing of product features, and the cloud architecture behind the product. You'll operate across a complex multi-cloud environment (AWS & GCP) spanning traditional VMs and modern managed and unmanaged container-based architectures, partnering with fellow Penetration Testing and Cloud Security engineers to run targeted assessments during the testing window immediately before each release. The role reaches beyond the application layer into the Control Plane, reviewing cloud configurations, IAM policies, and orchestration layers against security baselines, and extends to the frontline of external defense by triaging bug bounty submissions and outside vulnerability reports. AI and large language models are core to how this team works day to day — you'll use them to accelerate reconnaissance, generate attack vectors, analyze configurations, and draft vulnerability reports, while applying human judgment to validate findings and communicate risk clearly to product teams. Speed matters here: the team's operating cadence is built around identifying, validating, and reporting vulnerabilities quickly enough to keep pace with release velocity.

Outcomes & KPIs

Key Outcome(s) Owned

Ensure new product features and the underlying multi-cloud (AWS/GCP) infrastructure are rigorously security-tested before release, and that vulnerabilities surfaced internally or via bug bounty are triaged and communicated with speed and precision.

Success Metrics / KPIs:

Percentage of roadmap features assessed within the pre-release testing window.

Mean time to triage and validate bug bounty / external vulnerability reports.

Reduction in critical/high-severity vulnerabilities escaping to production post-release.

Time saved per assessment cycle through AI-assisted tooling and automation.

Quality and actionability of vulnerability reports and PoCs, as rated by product teams.

What You'll Do

Conduct deep-dive penetration tests of products across a multi-cloud (AWS & GCP) environment, working in tandem with a peer pentester.

Review IAM policies, service configurations, and cloud-native permission structures across the Control Plane to ensure cloud configurations meet security baselines.

Execute dynamic testing against web interfaces and API endpoints (Data Plane & Web UI).

Assess the security posture of hybrid infrastructure spanning containers and virtual machines.

Triage findings, build clear and reproducible proofs-of-concept, and partner with product teams to explain risk and drive remediation.

Use AI and large language models to automate reconnaissance, generate attack vectors, analyze configurations, and draft vulnerability reports, applying strong prompt-engineering skills to security contexts.

Monitor bug bounty pipelines and external reports, validating findings and managing researcher communication.

Functional Competencies

Required

Multi-Cloud Fluency: Deep architectural understanding of GCP and AWS. Capable of pivoting seamlessly between providers, performing manual configuration reviews of complex IAM/Resource hierarchies, and leveraging native APIs or modern CSPM frameworks to validate security controls.

Container Security: Proven experience auditing and hardening managed container services (GKE Autopilot/Standard, EKS, ECS) and self-hosted/unmanaged workloads (K8s, k3s, OCI-runc).